Statistical modeling systems input historical or known data and output a model or decision based on the input data. For example, a statistical distribution function may be output where the exact “shape” of the function depends upon one or more parameters (e.g., the first parameter of the distribution function has a first value determined by the statistical modeling system, the second parameter has a second value, etc.). In one example, a linear model is output where the linear model is described by the function y=β0+β1x+ε and the parameters in that example are β0 and β1. In general, the more information input to a statistical modeling system the better the quality of the resulting model. However, there may be a number of issues which prevent additional information from being used. For example, a set of known or historical data may be owned or managed by an entity that is unwilling to share information because of competitive reasons and/or legal reasons (e.g., the information may include sensitive personal and/or financial information). It would be desirable to develop statistical modeling systems that overcome some of these issues so that more information can be used.